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R

After a few months of tinkering, I’ve finally learned how to pull tweets with their geotags!

There are tons of different ways of going about this, but I decided to do it using the open sourced statistical software R. If you are interested in learning how I did it, shoot a comment below and I’ll follow up with my steps.

Since there is already a bike theme developed on this blog, I decided to map #bikeLA tweets. Using R, I pulled the latest 537 public tweets using the hashtag “#bikeLA”. The unfortunate reality is that 95% of these tweets had no location data 😦 But that didn’t keep me from mapping!

The central question that has driven this twitter spatial analysis, and many of the maps on this blog so far, has been Where is cycling? In this specific case, Where is cycling in LA? I can still get at this by pulling tweets every few days, or including more popular LA bike related hashtags in my data mine, but I thought for the sake of going through the process, I’d move forward with this post and expand my analysis using what I learn along the way.

Cleaning up the data

After removing tweets with no geolocation, I was left with 26 tweets–none of which were retweets. Many of these tweets came from the same screen name. The breakdown is below.

Clearly the Los Angeles County Bicycle Coalition (@lacbc) is the most common user of #bikeLA that reveals its location. It makes sense that an organization would be the highest number here, as many individuals have privacy concerns around sharing location data with their tweets. Some sites, such as geosocialfootprint, go as far as letting you track any user’s geotagged tweets, even estimating of their home and workplace.

Mapping #bikeLA

Well, below is the final product, a map of #bikeLA. Click on any point to read the tweet, see the time it was posted, and the username.

Click image to zoom

Next Steps

Though much less geospatial data was available than I had hoped, my new ability to pull this data from twitter opens up many possibilities for future projects. Much work to be done to properly map the LA bike scene’s twitter presence!